Tableau Reviews

There are so many smart features baked into this product, it's hard to even rank them. I think what makes Tableau stand out over other software I've used is that it doesn't start with a visualization, then pump numbers into it: It starts with numbers, and then represents them as shapes on a canvas. The result is more akin to an artist painting on a canvas using numbers as the brushes and colors. As a result, it is the flexibility of the mark types, and how they interact with data types, that make this product stand out. Someone who wants to create a visualization need only imagine the intended output, then use the numbers to create the marks in that output.

A non-trivial example is that a number can be considered continuous or discrete, depending on the context. In some cases, you need to use the same number both ways in the same visualization (histogram, anyone?). The flexibility to specify how a number is interpreted in terms of how an axis/mark will be generated is visualization at a more fundamental level. It is a completely different experience than pointing Excel at a highly manipulated table to generate an inflexibly structured chart type.

The use case has been different from one organization to another. In most cases, the initial buy-in and value-add is at the analyst level. The freedom to calculate, then derive, then iterate - that never-ending cycle every analyst out there knows well - to do that, do it quickly, and in a way that is remarkably beautiful, is every analyst's wet dream. Even if an analyst never shares visualizations they create during the course of a project, the tool makes them better and faster at deriving insights of their own by virtue of everything data visualization is meant to do for humans - improve understanding.

For organizations that have the capital to take it further, beginning to push out the interactivity, reports, and resulting insights up the ladders, or out the branches of the organization, with buy-in to the more-expensive server options - well, those organizations wield a much greater force. The ability for decision makers whose decisions affect many lives, higher in an organization, or the net effect of decision makers who make thousands of small decisions every day - Tableau, used well, makes it easier to make higher quality decisions faster. The same can be said of any technology used well, to be fair, but Tableau’s beauty and speed to insight is unmatched.

In my case, I have also used Tableau as a report prototyping platform. Designing and implementing is so fast in Tableau, when working with business stakeholders who may not know the specifics of what they want, and will ultimately be using whatever reporting platform their corporate standard is on - Tableau is great for iterating through version after version, change after change, until a report is built that is exactly what the business needs. Then, specific requirements can be written for a report builder using that corporate technology - which is invariably slower to iterate on. By moving the prototyping and proof of concept to Tableau, the development hours and agile lifecycle can be decimated.

Connectivity seems to be a sticky point, but it's also a hard nut to crack at the level that I would love to see. Tableau is fast, razor sharp on the whole - WHEN you use an extract. The problem is querying the data to fill the extract is only as fast as the source system. The result is that when you start working with large volumes of data, you often must start finding creative ways to improve the performance of your query. Here's where it gets tricky. I almost exclusively use SQL Server as a source. When I want to create custom data for an analysis (or some ongoing report with complexity), I have the latitude to write custom SQL. The problem is that in order for Tableau to retrieve metadata, the query sent to the server arrives as a subquery like:

SELECT * from ([your custom SQL here]) x

Because of this, I can't use a host of very useful T-SQL techniques that improve query performance or clarity. No CTEs, no temp tables, etc. In some organizations, the argument is that if you want that kind of complexity, wrap it up in a stored procedure and call the procedure (which, yes, you can call sprocs in Tableau), but that comes with its own disadvantages, which I won't get into too much here. But that is not to mention not all report writers or analysts have the privileges to create or alter sprocs on a server within their organization.

In any case, depending on how much control you have over your database as a Tableau user, as well as the nature of the data you are pulling, you may find yourself having to be very creative just to get data TO tableau to create larger extracts.

I started using Tableau in version 7, around 2012.

Desktop deployment is a cinch. Server, I had no involvement with setting up.

The user community is extremely vibrant and engaged, especially for how (relatively) young the product is, so I have only had two occasions to call support. In both cases, they were resoundingly helpful and responsive.

Back in 2012, we evaluated it against QlikView and MicroStrategy. MicroStrategy was more complex than our organization needed, and Tableau won out on ease of use and feature set, but I don't really remember the grittier details.

Initial setup was simple and fast for both Desktop and Server, but, as I mentioned, I was not involved in Server setup.

In 2012, we used an in-house team. I was not deeply involved at the time, so I don't have much implementation advice. For a larger organization, Tableau has created a consulting arm specifically for implementation, and having read a few of the white papers put out by them, I would highly recommend using them for a large implementation.

ROI can only be attained by use, so the ROI will be a function of adoption, not features of the product. Make sure you have the culture and an execution strategy to get people engaged and using it. Compared to other BI software, it's very easy to use, but not everyone will start using it just because there is a new icon on their desktop. Figure out adoption. Focus on it.

If people are using it, the ROI will be there, but if you spend 6-7 figures on an enterprise feature set and nobody uses it, it will have been wasted.

For the prototyping situation described earlier - one complex dashboard built from scratch then implemented in SSRS - the saved development time alone paid for the Desktop license.

This is a visualization software. Make sure you are looking at total cost of ownership in the context of other BI infrastructure that is still needed to get good ROI. Management of data at an enterprise level is more than just visualization, and if all of those things are in place, this product shines. If you have dirty data, slow resources, governance problems, etc., this software is not designed to solve those problems, and those problems will stunt the usefulness you get out of Tableau.

Tableau Desktop is equipped with so many valuable features that it is difficult to know where to begin. The functionality that allows users to join multiple source files and create visualizations using the fields from each of the joined source files is certainly nice to have. While the list of graphs and charts on the “Show Me” menu is impressive, one can do so much more with Tableau. With a little imagination and ingenuity, customized visualizations can be created easily and quickly.

It is far easier for my audience to grasp the key takeaways of an analysis by viewing a data visualization than by reviewing a spreadsheet. Tableau Desktop simplifies communication between analytics and senior executives.

I have not yet transitioned to Tableau Desktop 10.0, but I understand version 10.0 has functionality that allow users to perform cluster analysis. I am sure that I will be using this functionality frequently going forward.

I was introduced to Tableau as part of an online course on data visualization offered by the University of California, Irvine. Although I have been using Tableau for less than a year, I use the product frequently.

I have not encountered any deployment, stability or scalability issues.

Tableau provides an enormous number of online resources that are clear, concise, and very thorough. You are almost guaranteed to find the answers you are seeking within this online documentation.

We did evaluate a number of other BI solutions before selecting Tableau Desktop. In the end, we chose Tableau Desktop because of its flexibility and superior graphics. We are a fairly small organization. While we do not currently have a data warehouse, we are planning to build a BIDW within the next three years. Once the data warehouse has been rolled out, we will transition from Tableau Desktop to Tableau Server. In the era of big data, Tableau Server offers a number of attractive features including the built-in interface with both the R Project and various open source big data applications.

The initial setup for Tableau Desktop is about as straightforward as possible. Once you download the software to your computer, you are ready to use the application.

• Analytics
• Dashboarding
• Presentation
• Reporting

• Transitioned from static to dynamic reporting
• Transitioned from restricted to flexible visualizations

• Scheduling the reports as email to multiple users on daily basis preferably in Excel without creating user accounts for each user
  Establishing an effective connection from SAP BO universe to Tableau

I have used it for 3+ years.

I have not encountered any deployment, stability or scalability issues. I recommend filtering data at the source itself instead of bringing data into the tool and then applying filters.

Technical support is excellent. I hope they continue doing the same.

We previously used another solution. We switched to Tableau because, in my opinion, it has some of the best features available. It will take five years for other tools to catch up to where Tableau is right now.

Initial setup complexity was due to the organization's data structure, but it had nothing to do with the tool.

Implementation was in-house; we read through the guide.

It is expensive but worth it. I would prefer a lower license cost or an increase in the allowed # of users per license.

Buy it, implement it and stick with it for a sure and quick ROI.

Easy visualization, with only drag & drop, double-click!

Yesterday: Excel -> pivot table -> graph ....think...think...think and re-work because of no insight.

Today: Double-click or drag & drop and see....see...find insight.

• Korean geographic map at the detail level
• Polygon map is a hot requirement from end users

Korean users want the Tableau default map function to be one more detailed level
when they would visualize Korean territories.
----------------
Country : South Korea
Great area(OOO-do) : Seoul city, Busan city, KyungKi-do, Chungchung-do,...
County(XXX-gu): Mapo-gu, Seocho-gu,.Gangnam-gu these are covered by Tableau 10.

It needs more detailed level (GGG-dong) that is Seocho-dong, Minrak-dong, Woomyun-dong as these are not covered yet.

I have been using Tableau for six months.

DB speed, but it's a complicated issue that could be caused by Oracle? Excel? Tableau? N/W? etc...

I rate the level of customer service and technical support 9/10.

Initial setup was easy: Download the software and drag an DB file(i.e. excel) onto the Tableau icon.

That's it. There is no easier way to get started.

End users should "study" the software.
Do not wait for the IT department any longer.
Do it yourself.

Return = time saving, efficiency.
Investment = license fee & study time.

When you consider how much time is wasted on DB work, including visualization, the license fee is a small issue.
Unfortunately, many people are concerning only "the cost of software".
They miss "the hidden in-efficiency".

At first, buy one or several copies (not 10's or 100's).

Be an information worker who see and understand data by yourself without waiting an IT department support.

Then, expand later

The most valuable feature of this product is drag-and-drop visual analytics.

By deploying Tableau Server with an interactive dashboard built with Tableau Desktop, our company has gone through a journey of enabling self-analysis, and adopting a data-driven decision-making culture.

As a franchise model, we have enabled our franchisees and master franchisees to prepare self-service financial and operational reports to support their day-to-day operations.

• Better integration with R. Currently, users need to start R before running R scripts in Tableau. Ideally, it would be great if Tableau could save the step of firing up R to start with.
• Introducing more quite-common advanced analytics functions in Tableau. To enable users to perform simple advanced analytics at their fingertips.

I have been using Tableau for three years.

In terms of stability, we encountered compatibility issues when we upgraded the server version from 8.3 to 9.1. Several reports encountered error messages and were not able to render properly. Later, it was resolved by the server administrator together with Tableau support.

We were using Excel-based solutions. Tableau was much more advanced and user-friendly at that time.

Pricing is certainly a bit expensive.

For smaller organizations, Tableau Online would be a better solution. It is always up to date with the latest version, and no complex administrative duties are involved.

For bigger organizations that prioritize data security over cloud infrastructure, Tableau Server could be considered, which would allow full control by the organization.

Ease of use (including frequently used calculations), drag and drop and interactive data visualization are the most valuable features of the product to me.

• Helped organization to identify the best time to roll out the campaign for summer cruise booking.
• Measured health plan product performance to identify health plan product(s) where organization is losing or making money.
• Source-to-destination mapping for health plan members to determine how far members travel to their primary care physician’s office from their residence to identify opportunities for service quality improvements.

We need a Tableau connector to connect to other BI tools like SAP BusinessObjects.

I have been using this product for over three years.

So far, I have never encountered any issues with deployment or stability. I do feel slowness rarely when I try to get data directly by connecting to Teradata database using SQL Query.

Technical support is excellent.

I did a POC with Tableau for my current organization and compared this tool with other BI tools.

I recommended Tableau for the following reasons: truly mature product, price-performance balance, ease of use, lot of flexibilities in regrouping the data on the fly, most of the frequently used calculations are built-in and very easy to use - unlike some other BI tools, which are quite clumsy - and for best interactive data visualization capabilities. Most importantly, a non-IT person can develop a simple dashboard without any IT help.

Initial setup was very straightforward.

I installed the Tableau desktop on my computer. Tableau servers are installed by our internal admins. It’s an easy installation and doesn’t need the vendor’s help.

Sometimes admin gets overwhelmed after Tableau is rolled out in the organization as users get up to the speed in a very short period of time, because of how easy it is to use the tool. Therefore, system access and resource planning should be done and properly planned ahead of time.

People should be aware of the fact that Tableau doesn’t have a semantic layer. It takes a good amount of time to prepare the dataset / data structure. Once the dataset is ready, the data visualization part doesn’t take much time, even for a fairly complex dashboard, because the tool is very intuitive and easy to use.

It provides access to many kinds of data sources. For example: big data/SAP BW.

The second-most valuable feature is the wonderful usage experience. You cannot find this on any other vendor’s solution such as Microsoft or SAP. Even though Qlik’s QlikView is similar.

We use it for a very complex dashboard design showing our raw material trend analysis. Even though there is huge amount of data and information in these dashboards, Tableau easily provides high-quality UI presentations, along with quick response and design times.

Its server lacks traditional BI solution capabilities such as job scheduling, HA and etc. If you want to roll out it as an enterprise-wide application, you must consider many usage scenarios and operation-level items. Tableau has a robust design UI and presentation layer, but lacks many of the capabilities of an enterprise BI solution. We have been using the SAP BO BI solution for many years. We feel Tableau Server still has a long way to go.

I have used this solution for nearly one year.

I have had poor experiences using its mobile app when I demo some dashboards to high-level executives. Sometimes, it does not respond with results very quickly. But, the web UI is OK. I don’t know why there is a discrepancy.

Technical support has been good so far.

We have used SAP BO BI for many years. We liked the WebI /BO dashboard. We also evaluated Microsoft PowerBI and QlikView. Finally, our IT and project team chose Tableau because its UI/user experience is the best.

Its initial setup is simple, but server installation took some time to finish. We use Desktop and Server on our Windows platforms.

We have a local partner to support us. But, we also try each product by ourselves. A vendor partner provides some technical support or Q&A.

ROI has been good so far.

They must understand their real business goal and user’s needs or behavior for using the dashboard design. That impacts your tool’s usage and design approach. Try using Tableau Desktop anyway. Pay more attention to the Tableau community’s sharing or other experts’ design sharing on the website. It will give you many ideas or best design practices and reference.

Desktop – primarily ease of use, TTM, for ad-hoc and reusable analyses and visualizations.

Primarily TTM. The product is used by a number of different groups throughout the company – marketing, services, product engineering...

Server scalability and pricing. Tableau was considered but rejected for a large scale in-house analysis and reporting solution. Even with a large-scale implementation (eight-plus cores), it was decided that Tableau probably wouldn’t scale to the level needed and at that level, was costly.

Desktop was brought into the company five or six years back. Server instances soon followed to support smaller groups.

Desktop installation is easy and straightforward. Out-of-the-box usable.

We have a central IT group that handled server deployments and now handles corporate-wide desktop license maintenance and support with the vendor.

The desktop is fairly intuitive and easy to get started with. Training (on the product, data viz/scientist) is needed for deeper analyses.

As with any solution, do your homework. Understand what it is you’re trying to solve. Tableau is just one of many tools/solutions implemented across the company.